GIS5007 Google Earth Lab

 This is our last lab of the class.  Our lecture, prior to the lab, covered the future of cartography including neo-cartographers (those with a non traditional cartography background), 3D mapping, VGI (Volunteered Graphic Information), PPGIS (public participation GIS) and GeoTargeting. VGI has become widespread and it was very interesting to look at all the example sites that fellow students submitted. I love how VGI has been used in the area of citizen scientists which get the public involved and informed on important subjects. There are also some fun 'sightings' type sites for Bigfoot and the like. It was also amazing to realize just how much cartography has become woven into our everyday lives. Even to a scary degree with things like GeoTargeting which takes marketing to a "Big Brother" level. GeoTargeting can track your location within a meter for specialized marketing or products.

Our lab assignment was to create and interactive map and tour of south Florida using Google Earth Pro. which is a 3D interactive mapping environment. We first created our surface water map using ArcGIS Pro.

After this we used out converted KML files to create an interactive Google map of South Florida. You can see that interactive aspect allows you to zoom and click for pop-up information:

Once this map was created we used the Google Earth Pro tools to create a tour of several South Florida locations. This is  like a mini movie and there are a lot of options you can use if you choose to. Note the 3D quality of the images.

Google Earth Pro is not my favorite application for mapping but I can see where it can be useful and with more practice easier to get around in.

 

GIS5007 Isarithmic Mapping

This week we tackled Isarithmic Maps.  These maps depict smooth, continuous phenomena across an area, like precipitation for example. This is exactly what we we tasked with creating this week. Before creating our maps we first has to learn about the two different types of data; true point data where the values are measures at a point location, and conceptual data where values are collected over an area but are presumed to be point locations.

Next, we covered four different interpolation methods which are used to predict unknown values for a data set. The first was Inverse Distance Weight (IDW), second was Kriging, third was Splining and lastly was Triangulation.  For our lab we were provided with precipitation data which was downloaded from the USDA Geospatial Gateway. This data was derived and interpolated through the utilization of PRISM (Parameter-elevation Relationships on Independent Slopes Model).

With this data we first created a map using continuous tones. We changed the color scheme for our Annual Precipitation layer to Precipitation. Next, we added a hillshade effect layer. In this layer we edited the continuous color scheme giving it 6 colors with specific settings. This is the resulting map layout.

Our next step was to create a map using Hypsometric Tints. We used the same Annual Precipitation and Hillshade Effect layers in this map. We used the Int (Spatial Analyst Tool) and ran it on the Annual Precipitation raster to create a new layer. Once this was completed we removed the original Annual Precipitation and replaced it with this new one. The data was then manually classified into 10 classes and symbolized with a Precipitation color scheme. From  here we created contours using the Contour List Spatial Analyst tool. This is the resulting image.

Now having all the pieces we were tasked with putting together a final map layout using the cartographic design principles we learned in pervious labs.

  

GIS5007 Choropleth and Proportional Symbol Mapping Lab

 Our lecture this week introduced us to choropleth and proportional symbol mapping. We learned when they work best and in what situations to avoid them. We also covered the importance of color selection, map symbolization and data types relevant to creating an effective map of this type.

For our lab we used data complied in 2012 on population density and on wine consumption in Europe. Our data was presented in the Europe Albers Equal Area Conic projection. We created a layer for population density and asked to use everything we learned to select a color scheme fitting for out map, We had to utilize our skills to create appropriate SQL Query for Data Exclusion to get rid of data not relevant to the map. Examine different data classification systems and select the one we felt was most appropriate for our map. Create both proportional and graduated symbol layers for the wine consumption data, looked closely at each one to see how differently the data was presented and selected one. 

Next, we worked on fine tuning layers and creating a map layout making sure to include all of the essential elements. Form my may I utilized annotated labeling to have more control over my country labels avoiding overlap with my map symbology. I went with quantile data classification and graduated symbolization for the wine consumption layer. I also chose metric as my scale measure as metric was the measurement listed for the population density. I made the map extent box and leader line thin so that it would not compete with the main map.

After a great deal of minute adjustments, my creation was completed. Definitely not perfect but my skills are getting more refined.

GIS5007 M4 Data Classification Lab

 This week we were introduced to the two different types of data used in mapping. Qualitative which which differentiates between different types of things and Quantitative helps illustrate magnitude. We then covered the different data classification methods focusing primarily on Equal Interval, Quantile, Standard Deviation, and Natural Breaks (Jenks). The advantages and disadvantages of each one were discussed and how there is no magic formula for choosing a method. During this discussion we delved into the thematic map types; Choropleth, Proportional, Isopleth/Isarithmic, and Dot. These maps differ from general reference map in that display spatial data and not just geographic features. We learned about when to use each of them and what their drawback are. Another subject we touched on was the Modifiable Areal Unit Problem (MAUP). This is a statistical bias that happens when data is aggragated. The two types of biases are zonal and scale effects. A common modern example of how this can be a problem is Gerrymandering. 

For our assignment we were asked to make two different map layout compilations.  Each one containing 4 different maps with 4 different data classification methods to illustrate how the same data is represented differently. The subject matter for our maps was the over 65 population of Miami-Dade County in Florida. The first set is percent of population over 65 and the second was a population count normalized by area. I was not expecting it to be so difficult to chose a method of data classification. There are so many factors to consider it easily becomes overwhelming. As always, we have to keep the end user in mind and even after the data classification method has been chosen we still have to achieve good map balance. Below is the original map we were provided with and the two compilation layouts I created.

 

  

GIS5007 M3 Cartographic Design Lab

 This week we were introduced to land partitioning in the first part of out studies to gain a better understanding of land land partitioning systems.  We examined the history from meets and bounds to USPLS (United States Public Land Survey). We also looked at the changes that have come about with the advent of GIS and the trends toward more accurate corners being located and given latitude and longitude coordinates.

The other portion of this module was focused on the cartographic design process. First and foremost, always design your map with the end user in mind. We were introduced to Gestalt principles and how they relate to cartographic design. We delved into the implementation of visual hierarchy, utilization of contrast and establishment of figure-ground relationships. We looked at the layout to make sure that balance was achieved through appropriate placement of map elements and proper inclusion, exclusion. All of this has to come together in the creation of a good map.

For our lab we were given a very basic map and a set of guidelines. It was our job to put of this new knowledge to work and create a map with solid cartographic design principles.  I learned a lot in this exercise not the least of which was that it is more challenging than it sounds. Another important lesson was to keep in mind that you have to have a stopping point.  You could literally fine tune you map to eternity,

Here is my before and after:

     

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